What about @DeepMindAI 's protein folding success, using RL for data center cooling, WaveNet, etc, and their great neuroscience division? I'm surprised you are ignoring all of that and state that DeepMind is only about DRL
Google’s sibling DeepMind lost $572 million last year. What does it mean? Some thoughts I wrote for @Wired.https://www.wired.com/story/deepminds-losses-future-artificial-intelligence/ …
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i reported the sum of the revenue from all of those sources, and quietly hinted about some challenges in making them economically rewarding, in terms of computation, expense, and generalizability.
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So concerning the symbolic AI, is there concrete progress? You have an easy critique on deeplearning but it's the only solution that works. It is normal for businesses to spend billions for that. in 10 years, DL will be spread everywhere while no one will remember the Symb AI
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i have been advocating hybrids models, not purely symbolic solutions, fyi
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"Lost" would be more appropriate to describe the negative results of a company that was selling something. "Spent" would be better suited... And "Invested on research" would be best.
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advise you read the Alphabet report i linked; they and i used standard accounting technical terminology
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Good question: how much will Microsoft lose on a deal with OpenAI?
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Nvidia team just outperforms OpenAI models without any problem. Really funny investment.https://twitter.com/NVIDIAAIDev/status/1161678367818522624?s=19 …
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AGI will only be reached through interdisciplinary work that aims to understand consciousness through multiple lenses. Human cognitive science is the best way to dig into this area.
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should add that we need to step through the evolutionary development tree on our way, especially with embodied intelligence as we develop AGI google's current tensorflow chips have 65K ALUs which are like a neuron. thats 3 times that of a Lancelet.
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